5 Multivariable analysis

To create a nice display for multivariable models the multivariable model first needs to be fit.

By default, the variance inflation factor will be shown to check for multicollinearity. To suppress this column set vif=FALSE. Note: variance inflation factors are not computed (yet) for multilevel or GEE models.

glm_fit <- glm(orr~change_ctdna_group+pdl1+age,
               family='binomial',
               data = pembrolizumab)
rm_mvsum(glm_fit, showN = TRUE, vif=TRUE)

	OR(95%CI)	p-value	N	Event	VIF
change ctdna group		0.006	73	58	1.03
Decrease from baseline	Reference		33	19
Increase from baseline	23.92 (2.49, 229.77)		40	39
pdl1	0.97 (0.95, 0.99)	0.011	73	58	1.24
age	0.94 (0.87, 1.01)	0.078	73	58	1.23

p-values can be adjusted for multiple comparisons using any of the options available in the p.adjust function. This argument is also available for univariate models run with rm_uvsum.

rm_mvsum(glm_fit, showN = TRUE, vif=TRUE,p.adjust = 'holm')

	OR(95%CI)	p-value	N	Event	VIF
change ctdna group		0.018	73	58	1.03
Decrease from baseline	Reference		33	19
Increase from baseline	23.92 (2.49, 229.77)		40	39
pdl1	0.97 (0.95, 0.99)	0.022	73	58	1.24
age	0.94 (0.87, 1.01)	0.078	73	58	1.23